6 citations · 9 across the 20 of their papers we have counts for
6 papers · 1 filter
Spatial frequency information fusion network for few-shot learning
Wenqing Zhao, Guojia Xie, Han Pan +2
The objective of Few-shot learning is to fully leverage the limited data resources for exploring the latent correlations within the data by applying algorithms and training a model…
Feature Complementation Architecture for Visual Place Recognition
Weiwei Wang, Meijia Wang, Haoyi Wang +5
Visual place recognition (VPR) plays a crucial role in robotic localization and navigation. The key challenge lies in constructing feature representations that are robust to enviro…
Visual Explanation via Similar Feature Activation for Metric Learning
Yi Liao, Ugochukwu Ejike Akpudo, Jue Zhang +4
Visual explanation maps enhance the trustworthiness of decisions made by deep learning models and offer valuable guidance for developing new algorithms in image recognition tasks.…
Frequency-Adaptive Discrete Cosine-ViT-ResNet Architecture for Sparse-Data Vision
Ziyue Kang, Weichuan Zhang
A major challenge in rare animal image classification is the scarcity of data, as many species usually have only a small number of labeled samples. To address this challenge, we de…
Dynamic Accumulated Attention Map for Interpreting Evolution of Decision-Making in Vision Transformer
Yi Liao, Yongsheng Gao, Weichuan Zhang
Various Vision Transformer (ViT) models have been widely used for image recognition tasks. However, existing visual explanation methods can not display the attention flow hidden in…
Propensity-driven Uncertainty Learning for Sample Exploration in Source-Free Active Domain Adaptation
Zicheng Pan, Xiaohan Yu, Weichuan Zhang +1
Source-free active domain adaptation (SFADA) addresses the challenge of adapting a pre-trained model to new domains without access to source data while minimizing the need for targ…